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How Facebook went all in on AI
Facebook’s introduction of the News Feed in 2006 revolutionized the platform, providing users with a constantly updating stream of posts and status changes. Despite user complaints, engagement doubled. The company then implemented an algorithm called EdgeRank to prioritize content based on factors like age, engagement, and user connections. As Facebook embraced machine learning, it faced…
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AI is at an inflection point, Fei-Fei Li says
Fei-Fei Li, co-director of Stanford’s Human-Centered AI Institute, believes we are in an inflection moment for AI. Generative AI has caused the public to wake up to AI technology, leading to more businesses implementing AI in real-world products. Li discusses the risks of AI, the flaws of ImageNet, the role of data, and offers tips…
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Asymmetric Certified Robustness via Feature-Convex Neural Networks
The text discusses the proposal of the asymmetric certified robustness problem for deep learning classifiers, which addresses the vulnerability of these classifiers to adversarial examples. It introduces feature-convex classifiers as a solution to this problem, providing closed-form and deterministic certified radii for inputs. The text also highlights the theoretical promise of input-convex classifiers achieving perfect…
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Can Synthetic Clinical Text Generation Revolutionize Clinical NLP Tasks? Meet ClinGen: An AI Model that Involves Clinical Knowledge Extraction and Context-Informed LLM Prompting
Researchers from Emory University and Georgia Institute of Technology have developed CLINGEN, a generic framework for generating high-quality clinical texts in few-shot situations. By combining clinical knowledge extraction from knowledge graphs and large language models, CLINGEN improves the variety and distribution of synthetic clinical data. Experimental results show consistent performance increases across multiple tasks.
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Can Transformer Blocks Be Simplified Without Compromising Efficiency? This AI Paper from ETH Zurich Explores the Balance Between Design Complexity and Performance
Researchers from ETH Zurich have proposed modifications to simplify transformer blocks in deep neural networks without compromising training speed or performance. By combining signal propagation theory and empirical observations, they explored the removal of various components from standard transformer blocks. The proposed simplified transformers achieved comparable performance to standard transformers while using fewer parameters and…
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GitLab Introduces Duo Chat: A Conversational AI Tool for Productivity
GitLab has launched Duo Chat, a new tool integrated into its developer platform that aims to simplify the developer experience by leveraging conversational AI. The tool allows developers to have natural language conversations with the AI, providing code explanations, generating tests, and simplifying coding tasks. GitLab emphasizes a privacy-first approach and aims to make AI…
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A New Microsoft AI Research Proposes HMD-NeMo: A New Approach that Addresses Plausible and Accurate Full Body Motion Generation Even When the Hands may be Only Partially Visible
Researchers from Microsoft Mixed Reality & AI Lab have introduced a groundbreaking approach called HMD-NeMo (HMD Neural Motion Model) that generates accurate full-body motion in immersive mixed-reality scenarios, even when hands are only partially visible. HMD-NeMo uses a spatiotemporal encoder with novel mask tokens to encourage plausible motion, and it operates in real-time and online.…
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Meet SEINE: a Short-to-Long Video Diffusion Model for High-Quality Extended Videos with Smooth and Creative Transitions Between Scenes
The SEINE model is a short-to-long video diffusion model that generates high-quality extended videos with smooth and creative transitions between scenes. It focuses on generating intermediate frames between two different scenes to achieve seamless transitions. The model incorporates a random mask module and takes into account both visual and textual input to enhance the controllability…
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Research team builds AI robot to create oxygen on Martian surface
A team of researchers at the University of Science and Technology of China has developed an AI robot that uses Martian meteorite extracts to produce oxygen. The robot created a catalyst from the Martian rock samples to accelerate the process of extracting oxygen from water. This breakthrough demonstrates the potential of AI in supporting space…
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Nvidia unveils its new flagship chip, the H200, available in early 2024
Nvidia has announced the H200, a high-end chip designed for training AI models, with enhanced performance in inference. The chip is expected to be shipped in the second quarter of 2024 and will be compatible with existing systems using the H100. Nvidia’s stock has seen a 230% increase in 2023 due to the excitement around…